Work plan

  1. write up some stuff I need to know about MDV surface moisture and its behaviour in this RMD as input to the paper

  2. explore soil moisture dataset

    • data cleaning necessary?
    • understand surface moisture and temperature information distributions, determine cut-off value (0°C? -x°C?)
    • spatial configuration of loggers, i.e. think about validation strategy (how to do the spatial CV)
  3. data gathering for pre-study: find a cloud free day and get as many useful spatial predictor datasets as possible

  4. describe and understand relations between surface moisture and predictors & temperature

    • surface moisture and elevation
    • surface moisture and temperature
  5. build model for case study

  6. run workflow for the whole temporal and spatial setting

To do’s:

  • ask Pierre about salinity and pH-paper progress

Paper relevant info

Introduction

Research Question:

  • For Method 1 and 2: How accuarate can surface moisture be modeled for the open soil areas within the Antarctic Dry Valleys?

  • actually interesting question: Which factors does the spatio-temporal surface moisture configuration in the MDV depend upon?

What we know about surface moisture in the MDV

  • very low overall
  • longer wavelenghts can pick it up
  • short duration of hydrological events

Questions

  • should I only use values above 0 degrees? Find out when water freezes in the MDV and how the relation to salinity would be

Data

Calibration and validation

AWS and iButton spatial distribution

Already available:

  • iButton data

To download:

Example: Explorer’s Cove

There is:

  • Air Temperature
  • Precipitation
  • Solar Radiation
  • Relative Humidity (that’s what iButtons measure)
  • Soil Moisture
  • Soil Temperature
  • Wind Direction and Speed

Potential spatial predictors

Potential spatial predictors

Already available:

  • DEM 8 / 30m * TWI * slope
  • rock outcrop to use as a mask
    • use soil type map to find out where there is only rock and no soil
  • LST 30m
  • soil types
  • pH model (Pierre: “pH is very much correlated to soil moisture, and more linear than EC (because it’s already a log scale!), but I could also share EC estimates if need be.”)

To acquire

  • RS data:
    • SWIR
    • downscaled LST
    • radar
  • EC (Pierre)?

Methods

Method schematic overview

Discussion